ENGINEERING & SYSTEMS ARCHITECTURE

I build the data engines that power business intelligence.

Behind every analytics product is an engineering layer that makes the whole thing work — the pipelines, the transformations, the orchestration, the infrastructure. I design and build that layer. This is where I show how it's built.

660M
Records Ingested / Month
9.6B
Data Points Orchestrated
99.8%
Pipeline Uptime

This is what I build.

I'm Douglas Mallett. I run Amicus Data — a one-person data engineering and systems architecture operation that builds analytics products for professional services industries.

"There's no end to data, and there will only be more."

I build everything that makes an analytics dashboard possible. The pipelines that pull data from dozens of sources. The transformation layers that turn raw API responses into structured, queryable intelligence. The orchestration systems that keep the whole machine running on schedule. The data models and warehouse schemas that make queries fast and reliable. The frontend visualizations that make the output legible and useful.

I design the architecture, I specify the logic, I deploy the infrastructure, and I operate everything in production. This isn't an agency — it's an engineering operation where I own every decision from schema design to final deployment.

This site isn't selling services. It's a showroom — the lobby of the machine shop. The products I build live elsewhere, purpose-built for the industries they serve. This is simply where I show the engineering behind them.

Current Load Status

Let's talk about what's running right now.

Every month, my systems ingest 660 million records and orchestrate 9.6 billion data points across the platforms I've built. Not in a staging environment. In live production, powering analytics products that professionals rely on for real business decisions.

I engineered for this kind of volume from the beginning. The pipelines are built for massive throughput without degradation in speed or accuracy. When the data starts flowing, nothing breaks — because the architecture was designed for exactly this.

Data is elemental to business. Without data, there is no business.
Data engineering operations center with multiple monitoring displays
sensors SYSTEMS NOMINAL

"Data is easy to collect. Hard to trust. I engineer for trust — every pipeline, every transformation, every schema is in service of producing data that holds up under scrutiny."

Lifecycle Methodology

Extract. Transform. Load. Present. Optimize.

The fundamentals aren't complicated to explain. It's the execution that separates reliable data engineering from everything else.

01

Extract

I pull data from wherever it lives — APIs, databases, third-party platforms, legacy systems that nobody else wants to touch. If the data exists somewhere, I can get it and bring it into the ecosystem.

02

Transform

This is where raw data becomes structured intelligence. I clean it, normalize it, de-duplicate it, enrich it, and apply the business logic that transforms numbers into genuine meaning.

03

Load

Data flows into cloud warehouses with incremental updates that keep everything current without overwhelming the system. No lag, no stale reports, no wondering whether you're looking at yesterday's numbers.

04

Present

I build the frontend interfaces and connect to BI platforms — handling the last mile where data becomes something humans can see, explore, and act on. This is where all the backend work pays off.

05

Optimize

The work doesn't stop at launch. I monitor performance, identify bottlenecks, refine queries, and continuously improve the systems. The infrastructure gets better over time because I'm always watching.

Technological Capability

The whole stack. Soup to nuts.

I generalized across the entire data stack, then I went deep on every layer of it. That means my analytics products are built by one person who understands how all the pieces fit together — from data ingestion to final pixel.

Data Pipeline Engineering

Cloud-native systems on GCP, AWS, and Azure that move data reliably at any scale. Robust, monitored, designed to run without babysitting.

ETL & Transformation

Automated processing with Airflow, dbt, and custom tooling — standardizing formats, aggregating metrics, applying business logic, ensuring the data that lands in the warehouse is clean and usable.

Data Warehousing

BigQuery, Snowflake, PostgreSQL, Redshift — configured and optimized for the specific queries and workloads each product demands. Speed, cost, and scalability in balance.

Frontend & Visualization

Custom interfaces using React, Recharts, D3, and purpose-built dashboards. Custom visualizations, force-directed graphs, interactive data flows. The presentation layer gets the same attention as the backend.

AI & Agent Engineering

Autonomous agents for data classification, content analysis, competitive monitoring, and pipeline orchestration. The systems don't just process data — they make decisions about it.

Systems Architecture

This is where it all comes together. I design the entire information flow from extraction to presentation — every component communicating without friction or failure.

I build with tools — and I build systems that last.

Platform agnostic.
Fluent in everything.

I'm platform agnostic — not because I lack opinions, but because I've worked extensively across the entire modern data stack and I build with whatever makes the most sense for the product.

CLOUD PLATFORMS
Google Cloud / AWS / Azure
DATABASES & WAREHOUSING
BigQuery / Snowflake / PostgreSQL / Redis
ORCHESTRATION
Airflow / dbt / Prefect / Dagster
FRONTEND
React / TypeScript / Tailwind / D3

Architecture first.
Agent driven.

I design systems where intelligent agents handle the heavy lifting — extraction, classification, monitoring, optimization. The architecture is the product. Every pipeline, every transformation layer, every orchestration pattern is designed with precision and built to operate autonomously.

AGENT_ORCHESTRATOR::STATUS_ACTIVE
> Monitoring data event streams...
> Logic-based schema adjustment pending...
> Query latency optimized: -14%
> Integrity check complete. 0 errors detected.
"The world is a constant stream of data events. I just happen to be very good at catching them."

Vertical Expertise

Analytics products for professional services.

I build analytics platforms for industries where data genuinely matters — legal services, dental practices, accounting firms, financial advisors. Markets filled with accomplished professionals who need to understand their competitive position, their market share, and their digital footprint.

My analytics products deliver SEO intelligence, market share data, and competitive positioning insights. I build the dashboards, I engineer the pipelines, I design the information architecture — and then I deploy these products for the industries I serve.

Data engineering that runs while you sleep.

The systems are fully modularized, redundant, and built to run autonomously. Intelligent monitoring, automatic recovery, continuous optimization. This is smart tooling, built by someone who genuinely loves this work.

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